Computer Vision for Biodiversity Monitoring

This lecture covers the use of computer vision in global-scale biodiversity monitoring, addressing the decline in wildlife populations due to human activities. It explores the challenges of processing diverse biodiversity data, the importance of automating data processing using computer vision, and the application of deep active learning for species identification. The lecture also discusses the deployment of the MegaDetector system for wildlife conservation, the utilization of synthetic data to improve rare-class results, and the development of human-AI systems for wildlife monitoring. Future directions include incorporating multimodal data, domain expertise, and equitable technology in biodiversity monitoring methods.